1. Field of the Invention
This invention relates to a method and system for automated detection of clustered microcalcifications from digital images without reduction of radiologist sensitivity.
2. Discussion of Background
Mammography, along with physical examination, is the current procedure of choice for breast cancer screening. Screening mammography has been responsible for an estimated 30 to 35 percent reduction in breast cancer mortality rates. However, in 1996 approximately 185,700 new breast cancer cases were diagnosed and 44,300 women died from this disease. Women have about a 1 in 8 chance of being diagnosed with breast cancer, and 1 in 30 will die of this disease in her lifetime.
Although mammography is a well-studied and standardized methodology, for 10 to 30 percent of women diagnosed with breast cancer, their mammograms were interpreted as negative. Additionally, only 10 to 20 percent of patients referred for biopsy based on mammographic findings prove to have cancer. Further, estimates indicate the malignancies missed by radiologists are evident in two-thirds of the mammograms retrospectively. Missed detections may be attributed to several factors including: poor image quality, improper patient positioning, inaccurate interpretation, fibroglandular tissue obscuration, subtle nature of radiographic findings, eye fatigue, or oversight.
To increase sensitivity, a double reading has been suggested. However, the growing increase in the number of screening mammograms makes this option unlikely. Alternatively, a computer-aided diagnosis (CAD or CADx) system may act as a xe2x80x9csecond readerxe2x80x9d to assist the radiologist in detecting and diagnosing lesions. Several investigators have attempted to analyze mammographic abnormalities with digital computers. However, the known studies are believed to have achieved rates of true-positive detections versus false-positive detections that are undesirably low.
Microcalcifications represent an ideal target for automated detection because subtle microcalcifications are often the first and sometimes the only radiographic findings in early, curable breast cancers, yet individual microcalcifications in a suspicious cluster have a fairly limited range of radiographic appearances. Between 30 and 50 percent of breast carcinomas detected radiographically demonstrate microcalcifications on mammograms, and between 60 and 80 percent of breast carcinomas reveal microcalcifications upon microscopic examination. Any increase in the detection rate of microcalcifications by mammography will lead to further improvements in its efficacy in the detection of early breast cancer.
Although the promise of CAD systems is to increase the ability of physicians to diagnose cancer, the problem is that all CAD systems fail to detect some regions of interest that could be found by a human interpreter. However, human interpreters also miss regions of interest that are subsequently shown to be indicators of cancers. Missing a region that is associated with a cancer is termed a false negative error while associating a normal region with a cancer is termed a false positive error.
It is not yet clear how CAD system outputs are to be incorporated by practicing radiologists into their mammographic analyses. No existing CAD system can claim to find all of the suspicious regions detected by an average radiologist, and they tend to have unacceptably high false positive error rates. However, CAD systems are capable of finding some suspicious regions that may be missed by radiologists.
Accordingly, an object of this invention is to provide a method and system for automated detection of clustered microcalcifications from digital mammograms.
These and other objects are achieved according to the invention by providing a novel method and system for automated detection of clustered microcalcifications from digital mammograms in which a digital mammogram is obtained, parameters necessary for cropping the digital mammogram image are optimized, the digital mammogram is cropped based on the optimized cropping parameters to select breast tissue for further analysis, parameters necessary for detecting clustered microcalcifications are optimized, and clustered microcalcifications in the cropped digital mammogram are detected based on the optimized clustered microcalcification detection parameters.
The detected clustered microcalcifications are then stored as a detections image, the detections image is processed for display, and a computer-aided detection image is produced for review by a radiologist.
The radiologist first reviews the original mammograms and reports a set of suspicious regions of interest, S1. A CAD system, or more particularly, the CAD system of the invention, operates on the original mammogram and reports a second set of suspicious detections or regions of interest, S2. The radiologist then examines the set S2, accepts or rejects members of S2 as suspicious, thus forming a third set of suspicious detections, S3, that is a subset of set S2. The radiologist then creates a fourth set of suspicious detections, S4, that is the union of sets S1 and S2, for subsequent diagnostic workups. CAD system outputs are thereby incorporated with the radiologist""s mammographic analysis in a way that optimizes the overall sensitivity of detecting true positive regions of interest.